Highlights Propose a two-class monocentric urban model to address vehicle emission tax issues. Propose social welfare maximization model to determine optimal vehicle emission tax. Identify conditions that the rich or the poor lives in urban central area or suburb. Vehicle emission taxes may incur a change in residential segregation pattern. Vehicle emission taxes may also incur social inequity issue.

    Abstract Taxing vehicle emissions has been advocated as an effective measure to solve the smog and haze problems in China. This paper investigates the effects of vehicle emission taxes on residential segregation in a model of a monocentric city with two income classes. The proposed model explicitly considers the interactions among three types of stakeholders, namely the authority, property developers and heterogeneous households in terms of income level. The properties of the proposed model are analytically explored and the optimal vehicle emission taxes that maximize the social welfare of the urban system are determined. The conditions under which either the rich or the poor lives in the urban central area while the other class in the suburb are identified. The findings show that (i) a high emission tax can drive the low-income households to migrate from suburbs to urban central areas, and the high-income households to migrate from urban central areas to suburbs; (ii) the implementation of the vehicle emission taxes can effectively reduce the air pollution cost and increase the total social welfare of the urban system; and (iii) the emission tax policy may incur inequity issue in terms of change in utility levels of different income classes before and after introducing the vehicle emission taxes.


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    Title :

    Modeling the effects of vehicle emission taxes on residential location choices of different-income households


    Contributors:


    Publication date :

    2016-01-01


    Size :

    19 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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